
"""simple docstring"""


import torch

from transformers import AutoModel



class 	__a	(   torch.nn.Module						):






       def __init__(	self			:				str							,   UpperCAmelCase_			:				str="sayef/fsner-bert-base-uncased"      )->	Optional[int]:







              """simple docstring"""
              super(UpperCAmelCase_							,   self      ).__init__()

              UpperCamelCase       			=		AutoModel.from_pretrained(UpperCAmelCase_							,   return_dict=UpperCAmelCase_      )
              UpperCamelCase       			=		torch.nn.CosineSimilarity(3							,   1e-08      )
              UpperCamelCase       			=		torch.nn.Softmax(dim=1      )






       def 						_SCREAMING_SNAKE_CASE							(	self			:				str							,   **UpperCAmelCase_			:				int      )->	Dict:







              """simple docstring"""
              return self.bert(**UpperCAmelCase_      ).last_hidden_state






       def 						_SCREAMING_SNAKE_CASE							(	self			:				Union[str, Any]							,   UpperCAmelCase_			:				Tuple      )->	Any:







              """simple docstring"""
              return token_embeddings.sum(2							,   keepdim=UpperCAmelCase_      )






       def 						_SCREAMING_SNAKE_CASE							(	self			:				List[Any]							,   UpperCAmelCase_			:				Optional[int]							,   UpperCAmelCase_			:				Tuple							,   UpperCAmelCase_			:				Optional[Any]=1      )->	Union[str, Any]:







              """simple docstring"""
              return self.softmax(T * self.cos(UpperCAmelCase_							,   UpperCAmelCase_      )      )






       def 						_SCREAMING_SNAKE_CASE							(	self			:				Any							,   UpperCAmelCase_			:				Optional[Any]							,   UpperCAmelCase_			:				int      )->	int:







              """simple docstring"""
              UpperCamelCase       			=		W_supports["sizes"].tolist()
              UpperCamelCase       			=		W_supports["start_token_id"].item()
              UpperCamelCase       			=		W_supports["end_token_id"].item()

              del W_supports["sizes"]
              del W_supports["start_token_id"]
              del W_supports["end_token_id"]

              UpperCamelCase       			=		self.BERT(**UpperCAmelCase_      )
              UpperCamelCase       			=		self.BERT(**UpperCAmelCase_      )

              UpperCamelCase       			=		None
              UpperCamelCase       			=		None

              UpperCamelCase       			=		W_supports["input_ids"] == start_token_id
              UpperCamelCase       			=		W_supports["input_ids"] == end_token_id

              for i, size in enumerate(UpperCAmelCase_      ):
                     if i == 0:
                            UpperCamelCase       			=		0
                     else:
                            UpperCamelCase       			=		support_sizes[i - 1]

                     UpperCamelCase       			=		S[s : s + size][start_token_masks[s : s + size]]
                     UpperCamelCase       			=		S[s : s + size][end_token_masks[s : s + size]]

                     UpperCamelCase       			=		torch.matmul(q[i]							,   s_start.T      ).sum(1      ).softmax(0      )
                     UpperCamelCase       			=		torch.matmul(q[i]							,   s_end.T      ).sum(1      ).softmax(0      )

                     if p_starts is not None:
                            UpperCamelCase       			=		torch.vstack((p_starts, p_start)      )
                            UpperCamelCase       			=		torch.vstack((p_ends, p_end)      )
                     else:
                            UpperCamelCase       			=		p_start
                            UpperCamelCase       			=		p_end

              return p_starts, p_ends







"""simple docstring"""


import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_=7					)->				Optional[Any]:







       """simple docstring"""
       UpperCamelCase       			=		None
       if token is not None:
              UpperCamelCase       			=		{"Accept": "application/vnd.github+json", "Authorization": F"Bearer {token}"}

       # The id of a workflow (not of a workflow run)
       UpperCamelCase       			=		"636036"

       UpperCamelCase       			=		F"https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"
       # On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
       url += F"?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"

       UpperCamelCase       			=		requests.get(UpperCAmelCase_		,   headers=UpperCAmelCase_					).json()

       return result["workflow_runs"]



def 						lowerCamelCase__      (				UpperCAmelCase_					)->				Any:







       """simple docstring"""
       UpperCamelCase       			=		get_daily_ci_runs(UpperCAmelCase_					)
       UpperCamelCase       			=		None
       for workflow_run in workflow_runs:
              if workflow_run["status"] == "completed":
                     UpperCamelCase       			=		workflow_run["id"]
                     break

       return workflow_run_id



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)->				int:







       """simple docstring"""
       UpperCamelCase       			=		get_last_daily_ci_runs(UpperCAmelCase_					)
       if workflow_run_id is not None:
              UpperCamelCase       			=		get_artifacts_links(worflow_run_id=UpperCAmelCase_		,   token=UpperCAmelCase_					)
              for artifact_name in artifact_names:
                     if artifact_name in artifacts_links:
                            UpperCamelCase       			=		artifacts_links[artifact_name]
                            download_artifact(
                                artifact_name=UpperCAmelCase_		,   artifact_url=UpperCAmelCase_		,   output_dir=UpperCAmelCase_		,   token=UpperCAmelCase_					)



def 						lowerCamelCase__      (				UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)->				Optional[int]:







       """simple docstring"""
       get_last_daily_ci_artifacts(UpperCAmelCase_		,   UpperCAmelCase_		,   UpperCAmelCase_					)

       UpperCamelCase       			=		{}
       for artifact_name in artifact_names:
              UpperCamelCase       			=		os.path.join(UpperCAmelCase_		,   F"{artifact_name}.zip"					)
              if os.path.isfile(UpperCAmelCase_					):
                     UpperCamelCase       			=		{}
                     with zipfile.ZipFile(UpperCAmelCase_					) as z:
                            for filename in z.namelist():
                                   if not os.path.isdir(UpperCAmelCase_					):
                                          # read the file
                                          with z.open(UpperCAmelCase_					) as f:
                                                 UpperCamelCase       			=		f.read().decode("UTF-8"					)

       return results





